plot_series(*series, labels=None, markers=None, colors=None, title=None, x_label=None, y_label=None, ax=None, pred_interval=None)[source]#

Plot one or more time series.

This function allows you to plot one or more time series on a single figure via series. Used for making comparisons between different series.

The resulting figure includes the time series data plotted on a graph with x-axis as time by default and can be changed via x_label and y-axis as value of time series can be renamed via y_label and labels explaining the meaning of each series via labels, markers for data points via markers. You can also specify custom colors via colors for each series and add a title to the figure via title. If prediction intervals are available add them using pred_interval, they can be overlaid on the plot to visualize uncertainty.

seriespd.Series or iterable of pd.Series

One or more time series

labelslist, default = None

Names of series, will be displayed in figure legend

markers: list, default = None

Markers of data points, if None the marker “o” is used by default. The length of the list has to match with the number of series.

colors: list, default = None

The colors to use for plotting each series. Must contain one color per series

title: str, default = None

The text to use as the figure’s suptitle

pred_interval: pd.DataFrame, default = None

Output of forecaster.predict_interval(). Contains columns for lower and upper boundaries of confidence interval.

axmatplotlib axes, optional

Axes to plot on, if None, a new figure is created and returned


It manages the final visual appearance and layout. Create a new figure, or activate an existing figure.


Axes containing the plot If ax was None, a new figure is created and returned If ax was not None, the same ax is returned with plot added


>>> from sktime.utils.plotting import plot_series
>>> from sktime.datasets import load_airline
>>> y = load_airline()
>>> fig, ax = plot_series(y)